Ejemplo n.º 1
0
def test_case_5():
    data = {
        "eos": ec.EquationOfState(),
        "H": (85.006655, 322.612908, 218.840437)
    }

    return data
Ejemplo n.º 2
0
def test_case_2():
    data = {
        "muon_eqn_const":
        0.029956297154719348,
        "n_e":
        0.01,
        "n_mu":
        0.002111682234292741,
        "n_p":
        0.012111682234292741,
        "eos":
        ec.EquationOfState(t0=1.0,
                           t1=0.5,
                           t2=1.0,
                           t3=2.0,
                           x0=1.0,
                           x1=0.5,
                           x2=1.0,
                           x3=2.0,
                           sigma=1.0),
        "n_b":
        0.2,
        "del_mu":
        55.29173887061031,
        "mu_e":
        131.52051524885195,
        "min":
        -76.22877637824163,
        "n_e_min":
        np.array([0.001266337575998989]),
    }

    return data
Ejemplo n.º 3
0
def test_case_4():
    data = {
        "eos": ec.EquationOfState(),
        "n_b": np.array([0.2]),
        "x_e": np.array([0.0567969]),
        "x_p": np.array([0.0715545]),
        "x_mu": np.array([0.0147575]),
        "n_p": np.array([0.01431090]),
        "n_n": np.array([0.18568910]),
        "m_eff_n": np.array([1.60724175e-24]),
        "m_eff_p": np.array([9.68987117e-25]),
        "m_eff_L_n": np.array([1.261756e-24]),
        "m_eff_L_p": np.array([9.354640e-25]),
        "k_F_n": np.array([1.764964]),
        "k_F_p": np.array([0.751097]),
        "lambda": np.array([5.997578e-12]),
        "xi_n": np.array([7.511429e-12]),
        "xi_p": np.array([1.762823e-12]),
    }

    return data
Ejemplo n.º 4
0
def test_case_3():
    data = {
        "eos": ec.EquationOfState(),
        "n_b": np.array([0.1]),
        "x_e": np.array([0.0382232]),
        "x_p": np.array([0.0382232]),
        "x_mu": np.array([0.0]),
        "n_p": np.array([0.0038223]),
        "n_n": np.array([0.0961777]),
        "m_eff_n": np.array([1.64218807e-24]),
        "m_eff_p": np.array([1.19878858e-24]),
        "m_eff_L_n": np.array([1.445079e-24]),
        "m_eff_L_p": np.array([1.189092e-24]),
        "k_F_n": np.array([1.417420]),
        "k_F_p": np.array([0.483707]),
        "lambda": np.array([1.160505e-11]),
        "xi_n": np.array([1.259872e-11]),
        "xi_p": np.array([1.130619e-12]),
    }

    return data
Ejemplo n.º 5
0
    "Delta_p": gap_protons(k_F),
    "Delta_n": gap_neutrons(k_F)
})

df_gaps.columns = pd.MultiIndex.from_tuples(
    zip(df_gaps.columns, ["[1/fm]", "[MeV]", "[MeV]"]))
df_gaps.to_csv("./examples/data/energy_gaps.txt", index=False, header=True)

# ---- NRAPR EoS - parameters are taken from Steiner et al. (2005) ---- #

eos_NRAPR = ec.EquationOfState(
    t0=-2719.70,
    t1=417.64,
    t2=-66.687,
    t3=15042.00,
    x0=0.16154,
    x1=-0.047986,
    x2=0.027170,
    x3=0.13611,
    sigma=0.14416,
)

n_n_NRAPR = eos_NRAPR.n_n(n_b)
n_p_NRAPR = eos_NRAPR.n_p(n_b)
k_n_NRAPR = eos_NRAPR.k_F_n(n_b)
k_p_NRAPR = eos_NRAPR.k_F_p(n_b)
Delta_n_NRAPR = gap_neutrons(k_n_NRAPR)
Delta_p_NRAPR = gap_protons(k_p_NRAPR)
lambda_NRAPR = eos_NRAPR.lambda_L(n_b)
xi_n_NRAPR = eos_NRAPR.xi_n(n_b)
xi_p_NRAPR = eos_NRAPR.xi_p(n_b)